(untitled) (Research, Society and Development, 2020)
In the last five years, the number of Dengue cases has been growing sharply in the city of Garanhuns. The objective of this study was to determine an analysis of the time series of Dengue cases in the medium-sized municipality, associated with climatic factors that contribute to the occurrence of this disease with forecasts, thus facilitating better control and prevention. Methodology: The autoregressive model of seasonal moving averages with exogenous variables (SARIMAX) was applied, which is a linear regression model that involves a process of the SARIMA model. In addition to the graphical analysis of the decomposition of time series, the Dickey-Fuller test was used to assess the stationarity of the series. Considering the seasonal behavior and the non-stationarity of the time series, the adjusted model had as parameters the SARIMA model (p, d, q) (P, D, Q), applying the Akaike Information Criterion (AIC) to select the best model, using the software R. Result: Considering the seasonal component and the non-stationarity of the time series, the model with the best adjustment was SARIMA (0,1,3) (0.1.1), a significance level of 5% (p-value = 0, 01). The SARIMAX model (0, 1, 3) (0,1,1) plus the effect of temperature and humidity were adequate to report the incidence of Dengue. In the correlation, the increase in the temperature component was greater than the humidity in the number of Dengue cases.